000			02109nam a22002537a 4500
999			_c2385 _d2385
003			OSt
005			20191011114801.0
008			191011b ||||| |||| 00| 0 eng d
020			_a978-0-07-008770-5
028			_bAllied Informatics, Jaipur _c6745 _d4/10/2019 _q2019-20
040			_aBSDU _bEnglish _cBSDU
082			_a006.3 _bRIC
100			_aRich, Elaine
245			_aArtificial Intelligence
250			_b3rd
260			_aChennai _bMcGraw Hill Education (India) Pvt. Ltd. _c2017; c2009
300			_a568
500			_aThis book presents both theoretical foundations of AI and an indication of the ways that current techniques can be used in application programs. With the revision, most of the content has been preserved as it is, and an effort has been put in on adding new topics that are in sync with the recent developments in this field.
504			_aContents PART I: PROBLEMS AND SEARCH Chapter 1. What is Artificial Intelligence? Chapter 2. Problems, Problem Spaces, and Search Chapter 3. Heuristic Search Techniques PART II: KNOWLEDGE REPRESENTATION Chapter 4. Knowledge Representation Issues Chapter 5. Using Predicate Logic Chapter 6. Representing Knowledge Using Rules Chapter 7. Symbolic Reasoning Under Uncertainty Chapter 8. Statistical Reasoning Chapter 9. Weak Slot-and-Filler Structures Chapter 10. Strong Slot-and-Filler Structures Chapter 11. Knowledge Representation Summary PART III ADVANCED TOPICS Chapter 12. Game Playing Chapter 13. Planning Chapter 14. Understanding Chapter 15. Natural Language Processing Chapter 16. Parallel and Distributed AI Chapter 17. Learning Chapter 18. Connectionist Models Chapter 19. Common Sense Chapter 20. Expert Systems 416 Chapter 21. Perception and Action Chapter 22. Fuzzy Logic Systems Chapter 23. Genetic Algorithms:Copying Nature's Approaches Chapter 24. Artificial Immune Systems Chapter 25. Prolog-The Natural Language of Artificial Intelligence Chapter 26. Conclusion
650			_aComputer Science
700			_aKnight, Kevin
700			_aNair, Shivashankar B.
942			_2ddc _cBK